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- W2990977146 abstract "In some situations, research activities are conducted to measure the length of time until the event occurred. If it is possible to have not only the event of interest but also the competing events, then it is a kind of competing risks data. The main parameter of interest is the subdistribution function that shows the percentage of failing individuals due to a cause of interest. If the subdistribution needs to be predicted by predictor variables, then the regression model for competing risks data should be developed. In this paper, the regression model for the exponential Gompertz-like subdistribution is proposed. We use maximum likelihood estimation method to estimate the model parameters. Specifically, the subdistribution of the main event and all the rest competing events are estimated simultaneously. The proposed model was applied to the data of contraceptive discontinuation and gave a good result. Goodness-of-fit of the estimated regression model measured by the likelihood and Akaike Information Criterion (AIC) also gave the acceptable values." @default.
- W2990977146 created "2019-12-05" @default.
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- W2990977146 date "2019-11-01" @default.
- W2990977146 modified "2023-10-13" @default.
- W2990977146 title "A competing risks regression model based on the exponential Gompertz-like subdistribution" @default.
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- W2990977146 doi "https://doi.org/10.1088/1742-6596/1375/1/012072" @default.
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